The types of organisms present in an ecosystem profoundly influence its functioning, an idea well established for plants and animals, formalized in the state factor theory of ecosystem science, and illustrated through the impacts of plant and animal invasions on ecosystem processes. The physiological and taxonomic diversity of microorganisms far exceeds that of plants and animals combined. Yet, despite progress in applying molecular tools to analyze the microbial diversity of intact assemblages, the understanding of how individual microbial taxa affect ecosystem processes like element cycling remains weak. When applied to intact microbial assemblages, stable isotope probing (SIP) partly addresses this challenge, in that it physically links the fluxes of elements to an organism's genome.
Stable isotope probing (SIP) is a powerful technique for linking the genetic identity of microorganisms with their biogeochemical functioning in the environment. This is because the technique takes advantage of the particular biomolecules, namely, nucleic acids, where genetic identity and elemental composition (biogeochemistry) are literally physically connected. It is difficult to imagine a more incisive concept for linking element fluxes with genetic identity than a technique that monitors the uptake of traceable isotopes of elements into the molecules that record the genetic identity of organisms.
However, as developed and as practiced to date, the SIP technique is qualitative and does not provide quantitative measures of assimilation rates. Instead, SIP is only capable of differentiating between organisms that utilize a substrate versus those that do not. The distinction between labeled and unlabeled organisms is binary, defined by the density regions selected by the investigator, and thereby limiting the resolution of taxon-specific responses to labeled or unlabeled. The distribution of DNA along the density gradient reflects the influences of both isotope incorporation and GC (guanine-plus-cytosine) content, because the density of DNA increases with its GC content. Any comparison of density regions will reflect both influences, challenging inferences about quantitative isotope incorporation.
In conventional SIP, there are no assurances that the identification of the labeled community is complete. Low-GC-content organisms that incorporate the isotope label may not have shifted sufficiently in density to be part of the labeled density fraction, and high-GC-content organisms that do not incorporate the label may be erroneously inferred to be part of the labeled community. This could result in incomplete coverage when discrete, noncontiguous density intervals representing heavy and light fractions are selected for sequencing, omitting information about the microbial assemblage contained in the DNA at intermediate densities. Only the heavy fractions in both labeled and unlabeled treatments are sequenced and compared: any new organisms that appeared in the heavy fraction of the labeled treatment are inferred to have taken up enough of the isotope tracer to have shifted the density of their DNA. This approach could have excluded organisms that incorporated the isotope tracer but, because of their low GC content, do not shift sufficiently to be represented in the heavy fraction. In these ways. SIP as typically practiced is a qualitative technique capable of identifying some of the organisms that utilize a substrate and not a quantitative one capable of exploring the full range of variation in isotope incorporation among microbial taxa.